Reece Albert Stuart, Hulse Gary Kenneth
Division of Psychiatry, University of Western Australia, Crawley, WA, 6009, Australia.
School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, 6027, Australia.
Arch Public Health. 2022 Mar 30;80(1):101. doi: 10.1186/s13690-022-00813-6.
The epidemiology of cannabinoid-related cancerogenesis has not been studied with cutting edge epidemiological techniques. Building on earlier bivariate papers in this series we aimed to conduct pathfinding studies to address this gap in two tumours of the reproductive tract, prostate and ovarian cancer.
Age-standardized cancer incidence data for 28 tumour types (including "All (non-skin) Cancer") was sourced from Centres for Disease Control and National Cancer Institute using SEER*Stat software across US states 2001-2017. Drug exposure was sourced from the nationally representative household survey National Survey of Drug Use and Health conducted annually by the Substance Abuse and Mental Health Services Administration 2003-2017 with response rate 74.1%. Federal seizure data provided cannabinoid concentration data. US Census Bureau provided income and ethnicity data. Inverse probability weighted mixed effects, robust and panel regression together with geospatiotemporal regression analyses were conducted in R. E-Values were also calculated.
19,877 age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003-2017 of 124,896,418,350. Inverse probability weighted regressions for prostate and ovarian cancers confirmed causal associations robust to adjustment. Cannabidiol alone was significantly associated with prostate cancer (β-estimate = 1.61, (95%C.I. 0.99, 2.23), P = 3.75 × 10). In a fully adjusted geospatiotemporal model at one spatial and two temporal years lags cannabidiol was significantly independently associated with prostate cancer (β-estimate = 2.08, (1.19, 2.98), P = 5.20 × 10). Cannabidiol alone was positively associated with ovarian cancer incidence in a geospatiotemporal model (β-estimate = 0.36, (0.30, 0.42), P < 2.20 × 10). The cigarette: THC: cannabidiol interaction was significant in a fully adjusted geospatiotemporal model at six years of temporal lag (β-estimate = 1.93, (1.07, 2.78), P = 9.96 × 10). Minimal modelled polynomial E-Values for prostate and ovarian cancer ranged up to 5.59 × 10 and 1.92 × 10. Geotemporospatial modelling of these tumours showed that the cannabidiol-carcinogenesis relationship was supra-linear and highly sigmoidal (P = 1.25 × 10 and 12.82 × 10 for linear v. polynomial models).
Cannabinoids including THC and cannabidiol are therefore important community carcinogens additive to the effects of tobacco and greatly exceeding those of alcohol. Reproductive tract carcinogenesis necessarily implies genotoxicity and epigenotoxicity of the germ line with transgenerational potential. Pseudoexponential and causal dose-response power functions are demonstrated.
尚未运用前沿流行病学技术对大麻素相关的致癌作用进行流行病学研究。基于本系列早期的双变量研究论文，我们旨在开展探索性研究，以填补生殖系统的两种肿瘤（前列腺癌和卵巢癌）在这方面的空白。
利用SEER*Stat软件，从疾病控制中心和美国国立癌症研究所获取了2001 - 2017年美国各州28种肿瘤类型（包括“所有（非皮肤）癌症”）的年龄标准化癌症发病率数据。药物暴露数据来自物质滥用和精神健康服务管理局2003 - 2017年每年进行的具有全国代表性的家庭调查《全国药物使用和健康调查》，回复率为74.1%。联邦缉获数据提供了大麻素浓度数据。美国人口普查局提供了收入和种族数据。在R软件中进行了逆概率加权混合效应、稳健和面板回归以及地理时空回归分析。还计算了E值。
返回了19,877个年龄标准化癌症发病率。基于这些发病率和各州人口，这相当于在2003 - 2017年总计124,896,418,350的人口中有51,623,922例癌症病例。前列腺癌和卵巢癌的逆概率加权回归证实了因果关联，且在调整后具有稳健性。仅大麻二酚就与前列腺癌显著相关（β估计值 = 1.61，（95%置信区间0.99，2.23），P = 3.75×10）。在一个空间滞后一年和时间滞后两年的完全调整地理时空模型中，大麻二酚与前列腺癌显著独立相关（β估计值 = 2.08，（1.19，2.98），P = 5.20×10）。在一个地理时空模型中，仅大麻二酚与卵巢癌发病率呈正相关（β估计值 = 0.36，（0.30，0.42），P < 2.20×10）。在时间滞后六年的完全调整地理时空模型中，香烟：四氢大麻酚：大麻二酚的相互作用显著（β估计值 = 1.93，（1.07，2.78），P = 9.96×10）。前列腺癌和卵巢癌的最小建模多项式E值范围分别高达5.59×10和1.92×10。对这些肿瘤的地理时空建模表明，大麻二酚与致癌作用的关系是超线性的且高度呈S形（线性模型与多项式模型相比，P分别为1.25×10和12.82×10）。
因此，包括四氢大麻酚和大麻二酚在内的大麻素是重要的社区致癌物，它们叠加在烟草的影响之上，且大大超过酒精的影响。生殖系统致癌必然意味着生殖细胞具有遗传毒性和表观遗传毒性，并具有跨代潜力。展示了伪指数和因果剂量反应幂函数。
